23 citations · 27 across the 15 of their papers we have counts for
5 papers · 1 filter
Disentangling Shape and Pose for Object-Centric Deep Active Inference Models
Stefano Ferraro, Toon Van de Maele, Pietro Mazzaglia +2
Active inference is a first principles approach for understanding the brain in particular, and sentient agents in general, with the single imperative of minimizing free energy. As…
Fail-Safe Human Detection for Drones Using a Multi-Modal Curriculum Learning Approach
Ali Safa, Tim Verbelen, Ilja Ocket +3
Drones are currently being explored for safety-critical applications where human agents are expected to evolve in their vicinity. In such applications, robust people avoidance must…
Visualizing Convolutional Neural Networks to Improve Decision Support for Skin Lesion Classification
Pieter Van Molle, Miguel De Strooper, Tim Verbelen +3
Because of their state-of-the-art performance in computer vision, CNNs are becoming increasingly popular in a variety of fields, including medicine. However, as neural networks are…
Learning to Grasp from a Single Demonstration
Pieter Van Molle, Tim Verbelen, Elias De Coninck +3
Learning-based approaches for robotic grasping using visual sensors typically require collecting a large size dataset, either manually labeled or by many trial and errors of a robo…
Lazy Evaluation of Convolutional Filters
Sam Leroux, Steven Bohez, Cedric De Boom +5
In this paper we propose a technique which avoids the evaluation of certain convolutional filters in a deep neural network. This allows to trade-off the accuracy of a deep neural n…